Speech Software Engineer
Lead the design and implementation of a scalable, high-availability voice infrastructure that replaces legacy systems. Build and refine multi-threaded server frameworks capable of handling thousands of concurrent, real-time audio streams with minimal jitter and latency. Deploy robust ASR > LLM > TTS pipelines that process thousands of calls concurrently. Develop robust logic for handling media streams, ensuring seamless audio data flow between clients and machine learning models. Build advanced monitoring and load-testing tools specifically designed to simulate high-concurrency voice traffic. Partner with Speech Scientists and Research Engineers to integrate state-of-the-art models into a production-ready environment.
Senior Staff Systems Engineer
Drive the architectural vision for the GenerativeAgent product by designing and building a highly scalable, multi-agent platform for real-time voice and text customer service experiences across various industries. Act as a technical authority and advisor for multiple engineering teams, develop system design and technical roadmaps, and define communication, state management, and orchestration patterns for multi-agent systems. Design and implement scalable, multi-tenant deployment architectures, own and define system-level SLOs/SLIs focusing on latency, cost-efficiency, and fault tolerance, identify systemic risks with proactive mitigation strategies, partner with Security and Compliance teams to meet regulatory and security requirements, lead post-incident analysis and improvements, and collaborate cross-functionally with Product, Customer Engineering, Site Reliability Engineering, TPMs, and Research to translate business requirements into system designs and productionize ML research. Mentor senior engineers and communicate complex technical concepts to both technical and non-technical stakeholders.
Software Engineer, Backend
The backend developer will own major feature development and work directly with founders on product development from end to end. Responsibilities include working with a small interdisciplinary team across hardware, software, and design to build new products from scratch; building new features and designing new architecture to address challenging problems; building backend infrastructure to perform scalable training in the cloud; rethinking and refactoring existing codebases for scale; and continuously improving and maintaining code in production. The role involves full ownership throughout the entire product lifecycle, including idea generation, design, prototyping, execution, and shipping, contributing to multiple parts of the codebase in various programming languages.
Machine Learning Engineer
As a Machine Learning Engineer at Noetica, you will build ML models and pipelines with scalability and reproducibility as foundational principles, develop NLP systems that can accurately process and understand complex legal language and terminology, and design and implement LLM-based solutions that are well-documented and empower legal professionals to extract valuable insights. You will extend and create reliable model evaluation frameworks to ensure accuracy and reduce model drift or bias, simplify complex ML systems into more manageable solutions, optimize model performance through smart feature engineering and efficient algorithm selection based on actual use cases, and work with security engineers to implement responsible AI practices that protect sensitive data while delivering valuable insights.
Senior AI Security Engineer
Define and refine security workflows and incident response strategies. Design and implement advanced security use-cases. Build and automate simulations of complex attack scenarios and environments. Research security incidents and provide insights to enhance AI agents. Collaborate with cross-functional teams to integrate security solutions into the platform.
Software Engineer, Codex Runtime
The responsibilities include shaping the evolution of Codex by identifying how teams use and break AI-powered software engineering, driving changes across product, infrastructure, and model behavior to improve reliability. Building core team and enterprise primitives to enable Codex usability at scale, such as container orchestration, virtual machine provisioning/configuration, execution sandboxes, shared block storage, RBAC, admin and audit surfaces, usage and pricing controls, managed configuration and constraints, and analytics for visibility into Codex usage. Designing and owning secure, observable, full-stack systems that power Codex across web, IDEs, CLI, and CI/CD, integrating with enterprise identity and governance systems (SSO/SAML/OIDC, SCIM, policy enforcement), and developing data-access patterns that are performant, compliant, and trustworthy. Leading real-world deployments and launches by working with customers and go-to-market teams to roll out Codex across teams, using live usage and operational signals to iterate and improve the product and platform based on real-world feedback.
Freelance Software Developer (Kotlin) - AI Trainer
As an AI Tutor in Coding specializing in Kotlin development, the responsibilities include designing high-quality technical content, examples, and explanations demonstrating best practices in Kotlin development; collaborating with engineers to ensure accuracy and consistency across code samples, tutorials, and developer guides; exploring modern Kotlin frameworks and tools to create practical, real-world examples for learning and testing; and continuously refining content based on feedback, emerging patterns, and advances in the Kotlin ecosystem. The role also involves contributing to projects aligned with skills by creating training prompts and refining model responses to help shape the future of AI while ensuring technology benefits everyone.
Software Engineer, AI Video Agent
You will be building a new team in the US to develop the next generation smart AI video maker that can ingest user's content and compose quality videos for social media. You will work closely with product and marketing teams to quickly prototype, beta test, and produce the final version of this product using agent technology. The technology stack includes GCP, Typescript, Python, Redis, MongoDB, Cloud Storage, and various AI models. You will be involved in rushing prototype and production versions of this product, contributing to an innovative and ambitious project.
AI Engineer (New Graduate)
As an AI Engineer (New Graduate) at Distyl, you will design, implement, and deploy GenAI applications under the guidance of senior engineers, contributing to prompt design, agent logic, retrieval-augmented generation (RAG), and model evaluation to build full-stack AI applications that deliver measurable business value. You will gain exposure to customer-facing work by shadowing technical conversations and learning how business needs are translated into system design, with opportunities to take on more responsibility in technical decisions and implementation. You will partner with senior engineers to understand customer problems and translate requirements into technical solutions, participate in customer discussions, solution design sessions, and iterative delivery. Additionally, you will help improve Distillery, Distyl’s internal LLM application platform, by building reusable components, tools, and workflows and learn best practices for scalable, maintainable AI infrastructure. You will write clean, well-tested, observable production-quality code that meets reliability, performance, and security standards and learn how production AI systems are monitored, debugged, and improved over time. You will assist with evaluating AI systems across accuracy, latency, cost, and robustness, applying user feedback and metrics to improve system performance. Finally, you will continuously develop your skills in LLMs, software engineering, and AI through mentorship, code reviews, and hands-on project work, learning modern development workflows and deployment practices used in enterprise AI.
AI / ML Solutions Engineer
The AI / ML Solutions Engineer at Anyscale is responsible for designing, implementing, and scaling machine learning and AI workloads using Ray and Anyscale directly with customers. This includes implementing production AI / ML workloads such as distributed model training, scalable inference and serving, and data preprocessing and feature pipelines. The role involves working hands-on with customer codebases to refactor or adapt existing workloads to Ray. The engineer advises customers on ML system architecture including application design for distributed execution, resource management and scaling strategies, and reliability, fault tolerance, and performance tuning. They guide customers through architectural and operational changes needed to adopt Ray and Anyscale effectively. Additionally, the engineer partners with customer MLE and MLOps teams to integrate Ray into existing platforms and workflows, supports CI/CD, monitoring, retraining, and operational best practices, and helps customers transition from experimentation to production-grade ML systems. They also enable customer teams through working sessions, design reviews, training delivery, and hands-on guidance, contribute feedback to product, engineering, and education teams, and help develop reference architectures, examples, and best practices based on real customer use cases.
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